It is well known to use three-dimensional medical imaging techniques to obtain image data representative of structures within the body of a patient or other subject.
For example it is well known to use computerised tomography (CT) scanners to obtain three-dimensional image data representative of blood vessels or other structures. Usually, a contrast agent is injected into a blood vessel of the subject so that it passes through the blood vessels of interest. The presence of the contrast agent causes image data representative of the blood vessels obtained using the CT scanner to have a relatively high intensity and makes them easier to distinguish from surrounding tissue and other structures.
Blood vessels can also be imaged using a variety of other three dimensional imaging techniques, including for example MRI, PET or X-Ray Angiography.
A wide variety of techniques are known for the automatic processing of three dimensional image data in order to identify and model blood vessels and other branching structures. In many known techniques, the position of a centreline of the blood vessel or other branching structure is determined at a series of points along the structure, for example from analysis of the intensity profile of the structure. The points can then be joined or fitted to produce a centreline extending along the length of the blood vessel or other structure.
It can also be useful to determine contours, which represent the boundary of the blood vessels and other structures. For example, in the case of blood vessels, the contours can be used in subsequent procedures to automatically calculate the level of stenosis in a blood vessel from intensity levels and variations of image data representing points within the contours. Thus, rapid and accurate determination of contours can be important.
In some known techniques, contours for a series of points along a blood vessel are generated on planes which are largely perpendicular to the centreline of a blood vessel at those points. For each of the series of points along the blood vessel, a contour plane is determined, and the intensity profile of the data on that contour plane is analysed to determine the boundary of the blood vessel. The boundary at that point along the blood vessel is then represented by a contour.
However, although the centreline may be continuous, the curvature of the centreline is in general not smooth (the first derivative of the curve is not continuous). Although it is possible to smooth the centreline curve, for example by using a best fit algorithm, there is then a risk that the modified centreline would pass through calcium, or lie outside the vessel in some places. That point is illustrated with reference to FIGS. 1a, 1b and 1c. 
FIG. 1a shows a calculated centreline 2 of a blood vessel 4. It can be seen that the centreline is continuous but that it has sharp changes of direction along its length. The blood vessel includes a calcification or other obstruction 6. If the contour planes 7a, 7b, 7c, 7d, 7e, 7f, 7g (for example as illustrated in FIG. 1b) are taken as being perpendicular to the centreline at a series of points, it can be found that the resulting contours change direction too sharply. In some cases, contours determined just before and just after one of the changes of direction can overlap such that it can appear, incorrectly, that the blood vessel, represented by the contours, turns back on itself.
FIG. 1c shows the blood vessel 4 of FIG. 1a, but in this case the centreline has been smoothed. Whilst the smoothed centreline 8 may result in a smoothed series of contours, it can be seen that the smoothing has also resulted in the centreline 8 passing through the area of calcification rather than along the centre of the blood vessel 4.
It is possible for an operator to view images of the vessels or other structures overlaid with the calculated centrelines and contours, and to correct manually the position of the centreline or contours. However that can be time consuming and inefficient for the operator. Also, if the operator sees significant inaccuracies in the calculated centreline or contours, he or she may have reduced confidence in the image processing system that calculated the centreline or contours.
Vessels in the body are often in the form of tree-like structures such as that illustrated schematically in FIG. 2. The vessel structure of FIG. 2 comprises a root node 10 that leads to various leaf nodes 12, 14, 16, 18 via branch points 20, 22, 24. A vessel may be considered to be a path from a root node 10 to a leaf node 12, which can pass through one or more branch points, or part of such a path. A segment may be considered to be a section of the structure from one branch point to the next branch point (for example, from branch point 20 to branch point 22) or from the root 10 to the next branch point 20.
In some known systems, contours can be calculated for different blood vessels separately, which means that contours may be recalculated several times for sections of the structure that form part of different blood vessels. For example, the segment between branch points 20 and 22 will form part of a blood vessel between the root node 10 and leaf node 12, and will also form part of a blood vessel between the root node and leaf node 14. It can be particularly time consuming for an operator if they have to manually adjust contours for segment or part of a segment for one blood vessel when they have already manually adjusted contours for the same segment or part of a segment when considering another blood vessel.